AI Product Owner – Consultant

Infosys

AI Product Owner managing client-facing AI use cases and product vision for Infosys Consulting's Enterprise AI practice. Collaborating with cross-functional teams in a hybrid work environment.

Posted 6/3/2026full-timeWarsaw • 🇵🇱 PolandJuniorMid-LevelWebsite

Tech Stack

Tools & technologies

AWSAzureCloud

About the role

Key responsibilities & impact

Shape AI use cases — identify where machine learning, generative AI and agentic AI can solve real business problems, and equally where they cannot
Frame business cases and value hypotheses for AI products, including success metrics for probabilistic systems and the realistic costs, risks and dependencies
Own and prioritise the AI product backlog, translating ambiguous opportunities into well-scoped, testable increments that data science and engineering teams can deliver
Define product vision and roadmaps for AI-enabled products, balancing experimentation with production-grade delivery
Translate business problems into AI problems — specify data requirements, evaluation criteria, acceptance criteria and guardrails for ML and GenAI features
Advise on Responsible AI in everyday product decisions — fairness, transparency, accountability, human oversight and proportionate risk management
Guide AI products across the full lifecycle: ideation, data readiness, prototyping, evaluation, deployment, monitoring and continuous improvement
Engage business stakeholders, subject matter experts and end users to validate problems, test prototypes and drive adoption
Collaborate with distributed delivery teams, including offshore, to ensure quality and pace
Contribute to Infosys Consulting’s thought leadership, accelerators and reusable assets for AI Product Management

Requirements

What you’ll need

2+ years of hands-on Product Ownership experience (rising to 10+ at the more senior levels)
1+ years applying product ownership specifically to AI, ML or data products
Strong understanding of how AI, ML, GenAI and agentic AI differ from traditional software — particularly around probabilistic behaviour, data dependency, evaluation and monitoring
Demonstrable ability to translate business problems into well-framed AI problems, and back into measurable business outcomes
Experience working in Agile / Scrum delivery, owning a backlog and partnering with technical teams
Strong stakeholder management — comfortable engaging with both technical contributors and business leaders
Depth in at least one industry or one functional domain, with the curiosity and adaptability to operate credibly in new contexts
Working knowledge of Responsible AI principles — fairness, transparency, accountability, human oversight
Familiarity with current thinking in AI Product Management
Excellent written and verbal communication in English
Bachelor’s degree; quantitative or technical disciplines are an advantage
Willingness to travel — up to around 60% depending on project (UK and international)
A second major European language is an advantage
Functional depth in customer service, marketing, HR, procurement, finance, sales or IT operations
Awareness of specific Responsible AI frameworks — for example the EU AI Act, NIST AI RMF, or ISO/IEC 42001
Hands-on familiarity with model evaluation, prompt evaluation, RAG architectures, MLOps concepts and observability for AI systems (essential at Senior and Lead levels)
Knowledge of partner platforms — agentic workflow tooling, hyperscaler AI platforms (AWS, Azure, Google Cloud), modern data platforms
Consulting or comparable client-facing delivery experience
At more senior levels: experience leading distributed and offshore teams, shaping deal pursuits and developing junior talent
AI Product Academy certification
Certified Scrum Product Owner (CSPO) or SAFe Product Owner / Product Manager (POPM)
Hyperscaler AI/ML certifications — AWS, Microsoft Azure or Google Cloud
Responsible AI / AI governance credentials (e.g. IAPP AIGP)

Benefits

Comp & perks

About Enterprise AI
Health insurance
401(k) matching
Flexible working hours
Paid time off
Professional development opportunities

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Product OwnershipAIMachine LearningGenerative AIData ProductsAgileScrumModel EvaluationMLOpsObservability

Soft Skills

Stakeholder ManagementCommunicationCollaborationAdaptabilityCuriosity

Certifications

AI Product AcademyCertified Scrum Product OwnerSAFe Product Owner / Product ManagerHyperscaler AI/ML CertificationsResponsible AI / AI Governance Credentials